A Survey on Computational Approaches to the Discovery of microRNA Genes

Title:A Survey on Computational Approaches to the Discovery of microRNA Genes

Volume: 9 Issue: 2

Author(s): Ki-Bong Kim

Affiliation:

Keywords: Cell differentiation, gene expression, microRNA (miRNA), miRNA gene finding, miRNA target prediction.

Abstract: For quite a while, the main focus of molecular biology has been on DNA, being the carrier of the genetic code, with RNA being viewed merely as an intermediary player. However, lately it has become obvious that RNA plays much more important roles in the cellular regulatory mechanisms. The discovery of various new types of RNA has provided a further boost to RNA research. As a result, research into small regulatory RNA molecules and in particular microRNA (miRNA) has experienced an exponential gain in attention. miRNAs are short non-coding RNAs that regulate gene expression at the post-transcriptional level by directly cleaving targeted mRNAs or repressing translation. They are now recognized as one of the key regulators of gene expression, involved in almost every aspect of a cell life from cell differentiation to apoptosis. Since the discovery of the very first miRNAs, lin-4 and let-7, computational methods have been indispensable tools that complement experimental approaches to understand the biology of miRNAs. Computational approaches for miRNA studies can be classified into two main categories - miRNA gene finding and miRNA target prediction. This review focuses on miRNA gene finding, not miRNA target prediction that has been thoroughly reviewed in [1-5]. First, this paper briefly introduces the biological features of miRNA genes and summarizes the basic principles of in silico prediction. Next, concluding with some outlook and remarks, it provides a comprehensive survey of specific methods that have been proposed in the field.

Cite this article as:

Kim Ki-Bong, A Survey on Computational Approaches to the Discovery of microRNA Genes, Current Bioinformatics 2014; 9 (2) . https://dx.doi.org/10.2174/1574893608999140109113103